Nighttime Light Emissions Research Articles

Decoupling state of urban development and carbon emissions and its driving factors and predictions: A case study of Chengdu metropolitan area

Prioritizing the reduction of carbon emissions in key developing urban centers is a significant step toward achieving China's carbon peaking and neutrality goals. We examined the Chengdu metropolitan area as a case study. We proposed a coupled method for inversely estimating nighttime light and carbon emissions from energy consumption, enhancing the accuracy of fitting at the county scale and addressing the issue of missing energy consumption data. We integrated the Tapio decoupling model and the Logarithmic Mean Divisia Index (LMDI) model for comprehensive analysis, mitigating the limitations arising from the use of a singular model. Furthermore, we employed a multi-scenario analysis with an extended STIRPAT model to forecast the carbon emission trajectory of the Chengdu urban agglomeration and elucidate potential pathways for achieving carbon peaking and carbon neutrality goals. The findings indicated the following:(1)carbon emissions are predominantly concentrated in regions characterized by high levels of urban development. Forested land serves as the primary carbon sink; however, its capacity in the Chengdu metropolitan area fails to offset carbon emissions from energy consumption;(2)factor decomposition analysis revealed that economic development was the principal driver of carbon emissions, leading to an increase of 23.7964 million tons. Conversely, energy intensity emerged as the primary mitigation factor, reducing carbon emissions by 11.0677 million tons;(3)The Chengdu metropolitan area is projected to reach a carbon peak by 2030, with the multi-factor coordinated optimization (MFO) model representing the most favorable trajectory, with a projected peak of approximately 15.6998 million tons. However, to achieve carbon neutrality by 2060, there is still a surplus of approximately 10.4808 million tons.

Spatial assessment of nighttime anthropization in the Comoé National Park in Côte d’Ivoira (West Africa)

Abstract Protected areas play a crucial role in preserving biological diversity, providing ecosystem services, and regulating hydroclimatic processes. However, the environmental balance of these areas is increasingly under threat due to rapid population growth, high demand for natural resources, and the effects of global warming. To address this, sustainable management of protected areas is essential. This study aims to develop a methodology for monitoring and assessing levels of nocturnal anthropogenic aggression in the Comoé National Park (CNP) in Côte d’Ivoire. By using geospatial data from the Day/Night Band of the Visible Infrared Imaging Radiometer Suite (VIIRS/DNB), the study characterizes the nocturnal anthropization of CNP through the use of several indices. First, light reflectance density is used to identify nighttime light emission foci. Second, the lighted area density index (LADI) is employed to understand the nature of nocturnal activities taking place within CNP, as indicated by artificial light at night (ALAN). Finally, the light intensity index (LII) is used to evaluate the degree of influence of nocturnal anthropogenic activities on biodiversity. The study also found important activities through LADI and observed a high level of light pollution in CNP. Ultimately, the findings of this study indicate that there is a significant level of nocturnal anthropization within CNP, highlighting the need for effective management and conservation efforts in the area.

Quantifying nighttime light emission by land use from the stratosphere

The remote sensing of light pollution from a high-altitude balloon platform provides unique advantages to the study of nighttime light emissions. This method allows for inexpensive, high resolution, regional-scale mapping, while also providing color, time-dependent, and angular information that is not regularly obtained from orbital or low-altitude aerial platforms. Data collected for this analysis covered urban-to-rural areas within and surrounding the city of Indianapolis, Indiana, USA. Using zoning data, we show that land used for commercial purposes produces the highest quantity of light emission per area, although residential land emits the most light of any land use type primarily due to its large area. The quantity of emission from roads is within the range of previous results from the USA. We also compare these data with VIIRS DNB observations as a method of calibration and validation of our observations. The unique qualities of this method of nighttime remote sensing can provide detailed light emission data by land use to support crafting policy for the control of light pollution and improvement of the nighttime environment.

The built-up environment modulates the association of artificial night-time lights with the urban extent

ABSTRACT Artificial night-time light (NTL) emissions, collected by satellites, are a reliable and widely used remote proxy for urban extent. Recently, it was demonstrated that NTLs are stronger associated with the total volume of the buildings than with their total footprint area, a traditional urban extent measure. However, this finding may not be a general rule: We presume that both associations are sensitive to characteristics of the built-up environment, while the latter is known to be quite heterogeneous within and between cities. Moreover, we hypothesize that at least in specific built-up environments, NTL may even stronger correlate with another urban extent measure – the total lateral surface area of the buildings, due to its more accurate proportionality to the area of light-emitting windows. The present study uses NTLs and buildings datasets of 38 European capital cities and compares the associations of NTLs with the three aforementioned urban extent measures (the total footprint area, the total volume, and the total lateral surface area of the buildings) across different built-up environments. The results indicate that in urban areas characterized by a high density of tall buildings the strongest observed association is between NTLs and the building’s footprint area. In comparison, the total volume of buildings is better related to NTLs in urban areas that host compact settings of relatively small buildings. But there is a third type of physical urban configuration, characterized by large buildings sparsely distributed in space. In this type of urban area, the strongest observed association is between NTLs and lateral surface area. We conclude that monitoring urban growth using NTLs will benefit from a preliminary assessment of the local built-up characteristics.

Mapping the spatial-temporal changes in energy consumption-related carbon emissions in the Beijing-Tianjin-Hebei region via nighttime light data

The increase in carbon emissions exacerbates global warming and seriously threatens the sustainable development of human society. In China, energy statistics frequently suffer from missing and inconsistent data at the municipal or county level. Therefore, in the absence of statistical data, this study proposes a method of coupling nighttime light and energy consumption to invert carbon emissions at the grid scale, with high accuracy, which is suitable for spatial applications in developing countries in the context of the lack of energy-related carbon emission monitoring. We observed a good one-variable linear correlation between nighttime light and regional carbon emissions, with an average relative accuracy of 96.00%. The total carbon emission in Beijing-Tianjin-Hebei changed from 231 million tons in 2000 to 535 million tons in 2020. The overall carbon emission showed a "γ-shaped" pattern, with several high-density carbon emission centers. The hot spots spread from inland to the Bohai Coast and were concentrated in the "Beijing corridor Tianjin Tang", whereas the cold spots were mainly distributed in the northwest. The center of gravity of carbon emission shifted to the northeast, and Beijing and Tianjin considerably impacted the regional changes.

The global human settlement layer sets a new standard for global urban data reporting with the urban centre database

Monitoring of sustainable development goals (SDGs) requires a wealth of updated, reliable, and comparable data on planet Earth with respect to societal activities and society–environment interactions. Despite the massive big-data archives available today, salient data are missing for key thematic domains and geographical areas. Even for cities, which are the most prominent manifestations of human agglomeration, the data are scarce, sectoral, and scattered. Earth observation may help reconcile the disparities between data-rich and data-poor territories. The Global Human Settlement Layer (GHSL) project of the European Commission has generated an open-source global dataset on cities—the GHSL Urban Centre Database (GHS-UCDB). This database describes more than 10,000 Urban Centres in 2015, with their locations, extent, and sets of geographical, socio-economic, and environmental attributes, as well as multi-temporal data records (covering a time span of up to 40 years) (Figure 6). The database combines information extracted from satellite imagery with physical and socio-economic information from several voluminous and heterogeneous sources provided by researchers and institutions as open geospatial data. The paradigm introduced with the GHS-UCDB relies on massive geospatial data integration and harmonisation conducted in the GIS environment (mainly via spatial joins and zonal statistics). The range and depth of geospatial and statistical variables in this dataset represent a new standard foundation for information on cities—more than doubling the number of cities usually reported by international organisations and offering the capacity to understand dynamics, e.g., on population, greenness, economic productivity, night-time light, and pollutant emissions. Moreover, the database offers the basis to estimate SDG indicators and other essential variables for the Post 2015 Development Agenda.

Estimates of Power Shortages and Affected Populations during the Initial Period of the Ukrainian-Russian Conflict

Since the outbreak of the Ukrainian-Russian conflict on 24 February 2022, Ukraine’s economy, society, and cities have been devastated and struck on multiple fronts, with large numbers of refugees fleeing to neighboring countries. The lighting systems in Ukrainian cities have been severely restricted due to Russian missile bombing and curfew policies. The power shortages adversely affected the livelihoods of the Ukrainian residents dramatically. For a timely assessment of the power shortages’ extent and the affected population in Ukraine, this study tracked the dynamics of nighttime light emissions in Ukraine based on the newly developed daily Black Marble product (VNP46A2) from NASA. The results show that the average light radiance in Ukrainian urban areas has decreased by about 37% since the eruption of the war, with Kiev city being the most dramatic region, having a post-conflict decrease of about 51%. In addition, by introducing near-real-time population data, we have implemented a survey of the affected population in Ukraine suffering from war-induced power shortages. Estimates show that about 17.3 million Ukrainian residents were affected by power shortages. In more detail, the number of children under 10 years old was about 2.35 million (about 5.24% of the total population), while the number of elderly people over 60 years old was about 3.53 million (about 7.86% of the total population). Generally, the results of this study could contribute positively to the timely assessment of the impact of the conflict and the implementation of humanitarian relief.

Correlation Analysis of CO2 Concentration Based on DMSP-OLS and NPP-VIIRS Integrated Data

In view of global warming, caused by the increase in the concentration of greenhouse gases, China has proposed a series of carbon emission reduction policies. It is necessary to obtain the spatiotemporal distribution of carbon emissions accurately. Nighttime light data is recognized as an important basis for carbon emission estimation. A large number of research results show that there is a positive correlation between nighttime light intensity and carbon emission. However, in the current context of China’s industrial reforms, this positive relationship may not be entirely correct. First, we correct the nighttime light data from different satellites and established a long-term series data set. Then, we verify the positive correlation between nighttime light and carbon emission. However, the time scale of emission data often lags, and the carbon concentration data are released earlier and are more accurate than emission data. Therefore, we propose to investigate the relationship between nighttime light and carbon concentration. It is found that there may be different correlations between nighttime light and the carbon concentration, due to different urban industrial structure and development planning. Therefore, by exploring the relationship between nighttime light and the carbon concentration, the existing carbon emission estimation model can be modified to improve the accuracy of the emission model.

An extraversion affair: African states and the subnational locations of large-scale land acquisitions

ABSTRACT Since the 2008 financial crisis, international investments in farmland have attracted considerable academic attention, yet surprisingly little is still known about their subnational determinants. To uncover why foreign land deals are situated in a particular territory, I incorporate this empirical puzzle with arguments about African state dynamics in processes of large-scale land acquisitions (LSLAs). This article argues that African authorities use LSLAs as strategies of extraversion: ruling elites sell or lease large parcels of land in areas with weak state infrastructural capacity. By doing so, they assert their formal authority by granting formal land titles, while concurrently outsourcing their responsibility for public good provision to foreign investors. I empirically test my argument using recently improved satellite imagery and the subnational locations of 468 land deals in Sub-Saharan Africa between 2008 and 2018. Innovative spatio-temporal models are estimated, allowing for insightful contributions to current research on farmland investments, African statehood and research methods. Results confirm my theoretical expectations: night-time light emission, as a measure of subnational infrastructural capacity, is negatively associated with new LSLAs. In other words, LSLAs are located in areas with poor infrastructural capacity, so that African states can benefit from them to maintain themselves.

Nighttime lights, urban features, household poverty, depression, and obesity

Nighttime Light Emission (NLE) is associated with diminished mental and physical health. The present study examines how NLE and associated urban features (e.g., air pollution, low green space) impact mental and physical wellbeing. We included 200,393 UK Biobank Cohort participants with complete data. The study was carried out in two steps. In Step1, we assessed the relationship between NLE, deprivation, pollution, green space, household poverty and mental and physical symptoms. In Step2, we examined the role of NLE on environment-symptom networks. We stratified participants into high and low NLE and used gaussian graphical model to identify nodes which bridged urban features and mental and physical health problems. We then compared the global strength of these networks in high vs low NLE. We found that higher NLE associated with higher air pollution, less green space, higher economic and neighborhood deprivation, higher household poverty and higher depressed mood, higher tiredness/lethargy and obesity (Rtraining_mean = 0.2624, Ptraining_mean < .001; Rtest_mean = 0.2619, Ptest_mean < .001). We also found that the interaction between environmental risk factors and mental, physical problems (overall network connectivity) was higher in the high NLE network than in the low NLE network (t = 0.7896, P < .001). In areas with high NLE, economic deprivation, household poverty and waist circumference acted as bridge factors between the key urban features and mental health symptoms. In conclusion, NLE, urban features, household poverty and mental and physical symptoms are all interrelated. In areas with high NLE, urban features associate with mental and physical health problems at a greater magnitude than in areas with low NLE.

Evaluating Street Lighting Quality in Residential Areas by Combining Remote Sensing Tools and a Survey on Pedestrians’ Perceptions of Safety and Visual Comfort

The perceived quality of street lighting influences pedestrians’ perceptions of safety and visual comfort, as well as outdoors activities at night. This study explores the association between street lighting attributes, such as illuminance and wavelength, and pedestrians’ feeling of safety (FoS) and perceived lighting quality (PLQ) in eight residential districts in Dalian, China. To achieve this goal, we combine remote sensing technology with ground investigation. The ground research includes physical measurements of lighting attributes, such as intensity, color temperature, and glare, as well as survey evaluations of pedestrians’ perceptions of safety and visual comfort. We also analyze the influence of several environmental factors, such as traffic volumes and vegetation, while accounting for personal characteristics of the observers, such as gender and age. Findings from the remote sensing reveal that Dalian’s residential districts differ substantially by their nighttime light emissions, with high concentration of strong red band (i.e., long wavelength) emissions occurring in Zhongshan and Jinzhou, and strong blue band (i.e., short wavelength) emissions found in central Zhongshan. Results from the ground surveys further indicate that a satisfactory level of FoS reaches at the illumination levels of 5–17 lx, and that people feel safer if nighttime light is warm and uniform. From a multiple regression analysis, it is also found that illuminance and uniformity are the main factors affecting PLQ under conditions of low or high illuminance, while glare and color temperature play a more significant role under high illuminance. In addition, a satisfactory level of PLQ is found at illuminance levels of 25–35 lx and light color temperature of 4000 K–5500 K.

Quantifying the Disaggregated Impact of Atrocities on Socioeconomic Activity

Abstract Our understanding of cruelty's impact on global human security and socioeconomic outcomes is still limited, especially with regard to how these effects unfold at the local, as opposed to the country, level. In this study, I first review literature on the impact of conflict, and violence against civilians specifically, on economic and political development globally, explicating potential adverse impacts, and highlighting the possibility of such violence increasing resilience in the long term. I then identify and discuss pathways linking political violence with lower socioeconomic activity locally. I hypothesize that violence disturbs socioeconomic activity in multiple ways, including by hurting businesses and laborers, scaring away tourists, and decreasing local investment, while additionally arguing that if no new atrocities happen, any impacts generated by these pathways will be relatively short term. Empirically, to operationalize local socioeconomic activity, I rely on nighttime light emissions; to operationalize atrocities, I rely on data from the Worldwide Atrocity Dataset, which measures all events that resulted with at least five civilian deaths by location. To test my expectations, I estimate both ordinary least squares and generalized methods of moments (GMM) models on a grid—(0.5 × 0.5-degree resolution) year level sample for the years 1997–2013. I find that, on average, an additional atrocity event corresponds to a decrease of 3–10 percent in local development levels the following year, compared with the baseline, but that such impacts disappear by the fourth year after the incident. Building on these findings, I discuss in detail research and policy implications.

Estimating Local Inequality from Nighttime Lights

Economic inequality at the local level has been shown to be an important predictor of people’s political perceptions and preferences. However, research on these questions is hampered by the fact that local inequality is difficult to measure and systematic data collections are rare, in particular in countries of the Global South. We propose a new measure of local inequality derived from nighttime light (NTL) emissions data. Our measure corresponds to the local inequality in per capita nighttime light emissions, using VIIRS-derived nighttime light emissions data and spatial population data from WorldPop. We validate our estimates using local inequality estimates from the Demographic and Health Surveys (DHS) for a sample of African countries. Our results show that nightlight-based inequality estimates correspond well to those derived from survey data, and that the relationship is not due to structural factors such as differences between urban and rural regions. We also present predictive results, where we approximate the (survey-based) level of local inequality with our nighttime light indicator. This illustrates how our approach can be used for new cases where no other data are available.

Diverse neighbors and post-conflict recovery at the village level: Evidence from Iraq after ISIL

Why do some towns recover faster than others after intrastate conflict? Many important decisions about post-conflict recovery are made at the substate level, but little empirical work has investigated what causes differences in recovery outcomes within a country. This article suggests that proximity to ethno-religiously diverse neighbors slows a town’s post-conflict recovery. A town has ‘diverse neighbors’ if towns with different plurality ethno-religious groups are nearby. This hypothesis is tested by exploring variation in recovery speed among Iraqi towns after the 2014–17 Islamic State insurgency (ISIL). The article constructs 81-month panels of economic activity for 379 Iraqi settlements occupied by ISIL by using satellite-observed nighttime light emissions as a proxy for economic activity. The panels reveal large variation in post-conflict recovery among towns during the first year of peace. Village-level survey data are then used to construct a measure of neighbor diversity, which is combined with lighting-based recovery scores in spatial autoregression. The results show that greater neighbor diversity is robustly associated with slower settlement recovery. The neighbor diversity penalty cannot be fully explained by cleavages between groups ‘on opposite sides’ of the conflict; proximity to out-group neighbors appears to slow recovery even between wartime allies. Several explanations are considered, and this article suggests that the types of post-liberation controllers that arise in diverse areas – which tend to be substate militias rather than the government – may be one important mechanism.

Peculiarities of the environmental light pollution in Chernivtsi Region

Introduction. Every year industrial development and economic growth make light pollution worsen on a global scale. It is a well-known fact that artificial outdoor lighting causes destruction of wildlife habitat, impacts circadian rhythms of all living beings, disrupts animal behavior and leads to medical disorders of humans. Over the last decade scientists switched their focus from artificial sky glow over large cities to light pollution of rural landscapes, protected areas and roadways. &#x0D; The purpose of this paper consists in assessing night-time light emissions over Chernivtsi Region as well as over city of Chernivtsi using satellite measurements.&#x0D; Methods. Measurements of night-time light emissions were obtained with the help of GIS web application Radiance Light Trends and the light trends analysis tool. The application allows examination of changes in light pollution across selected areas since 1992 and performs time-series analysis with fitting an exponential curve into the data set.&#x0D; Results. The trend in light emissions observed by satellites for Chernivtsi Region indicated brightening at the rate of 2.45 % per year from 1992 to 2014, and 2.93 % per year from 2014 to 2021. The marked increase in the intensity of atmospheric light pollution over Chernivtsi Region is largely attributable to urban expansion of district centers, national &amp; international routes and resort complexes. At the same time, the spatial pattern of the light environment over city of Chernivtsi indicated a nearly constant level of aggregate annual light radiance for the last 8 years. A large irregularly shaped "light spot" was detected on the territory of the Prut-Siret interfluve. It crosses the region from the northwest to the southeast and covers the regional center with its suburbs and the national highway H-10. The night light radiance constitutes 47.49∙10-9 mW/cm2 sr in the center of the spot and more than 1∙10-9 mW/cm2 sr at its edges. The highest level of light pollution in Chernivtsi Region was registered in January, and the lowest – in March. Night-time light emission over two most illuminated highways remains relatively constant regardless of the season.&#x0D; Conclusion. The study highlights that despite low population and low economic activity, rural landscapes demonstrate a trend towards increasing brightness of the night sky. The findings provide a quantitative reference for light pollution management in the region and for further research in the area.

Turning the lights on to keep them in the fold: How governments preempt secession attempts

There are many regions that meet the necessary conditions for sovereign governance in the world, but few secessionist conflicts. I argue that this relative paucity of secessionist violence is the result of government preemption of potential secessionist movements. Using cross-national geospatial data from 1992 to 2013, I find that governments invest more, measured via nighttime light emissions, in more secession-prone regions. The same factors that make territory attractive for secession, such as large populations and international borders, also make governments willing to work to retain control of that territory, contributing to the scarcity of separatist civil conflicts.

Estimating economic activity of South African provinces using satellite technology: An econometric panel data application

This article studies the economic application of the remote sensing of night-time light emissions using satellite technologies within the South African context, focusing on its nine provinces as the unit of investigation. Observing human activity from outer space using satellite technology and remote sensing focusing on man-made light emissions presents real opportunity, especially where reliable national statistics are lacking. The methodology involves the estimation of panel data, autoregressive distributed lag and co-integration models that estimate provincial night-time light intensity as a proxy for provincial gross regional product (GDP). Both the ARDL and co-integrating models point to a long-run co-integrating relationship between GDP and night-time total light intensity, while the panel models suggest that the inverse Henderson elasticity for all provinces is 0.277 (cross-section fixed model). The ARDL models also establish a statistically significant short-term error correction term. The combined results suggest that a statistically significant long- and short-term relationship does indeed exist between provincial GDP and night-time lights within the South African and provincial context.

Remote night-time lights sensing: Investigation and econometric application

Orientation: Some recent studies have been published that demonstrated the value of remote sensing night-time lights as descriptors and/or proxies for human activity. Research purpose: This article investigated the association between night-time light emissions and gross domestic product (GDP) estimates for South Africa. Motivation for the study: Satellite night-lights data seemed to be a useful proxy for economic activity at temporal and geographic scales for which traditional data are of poor quality, are unavailable or only available with a large time lag. Research approach/design and method: The article primarily used the remote sensing of night-time light emissions using satellite technologies. The methodology employed in this study involved estimating both a vector error correction modelling (VECM) and autoregressive distributed lag (ARDL) models that map light growth into a proxy for GDP growth. Main findings: Both the VECM and ARDL models confirmed a long-term co-integrating relationship between GDP (per capita) and night-time lights (total light intensity), a statistically significant short-term error correction term could, however, not be established through the VECM, but indeed through the ARDL model. Practical/managerial implications: The results of the study suggested that satellite remote sensing technologies held much promise and opportunities in terms of the field of Economics and Development. Contribution/value-add: This study contributes to our understanding of the spatial and temporal behaviour and trends in economic activity. It also suggested the use of satellite remote sensing technologies as part of official statistical frameworks and methodologies.

Does building development in Dhaka comply with land use zoning? An analysis using nighttime light and digital building heights

Zoning is an important tool to regulate the use of land and to characterize built form over land, and thus to facilitate urban sustainability. Availability of reliable data is crucial for monitoring land use zoning, which contributes directly to the success of the Sustainable Development Goals (SDGs) in general, and SDG Goal 11 for sustainable cities and communities in particular. However, obtaining this valuable information using traditional survey methods is both costly and time-consuming. Remote sensing technology overcomes these challenges and supports urban policymaking and planning processes. This study unveils a novel approach to developing a cost-effective method for identifying building types using Sentinel-2A, Visible Infrared Imaging Radiometer Suite (VIIRS)–based nighttime light (NTL) data, and TanDEM-X–based Digital Surface Model (DSM) data. A newly developed index for this study, the Normalized Difference Steel Structure Index (NDSSI), is useful for rapidly mapping industrial buildings with steel structures. The implementation status of Dhaka’s existing land use plan was evaluated by analyzing the spatial distribution of different types of building uses. This study classifies residential, commercial, and industrial buildings within Dhaka using building height, and nighttime light emission. The experimental results reveal that about 67% of commercial and 51% of industrial buildings within the Dhaka Metropolitan Area (DMA) do not comply with the land use zoning by the Detailed Area Plan (DAP). It also reveals that approximately 10% of commercial buildings, 9% of industrial buildings, and 6% of residential buildings have encroached upon conservation zones (such as open space, flood-prone zones, water bodies, and proposed areas for future road extension). A major constraint in the study was the low spatial resolution of the nighttime light dataset, which made it difficult to distinguish individual sources of light. Still, the methodological approaches proposed in this study are expected to promote reduced costs and efficacious decision-making in urban transformation and to help achieve SDG 11, especially in developing countries.

Is Favoritism a Threat to Chinese Aid Effectiveness? A Subnational Analysis of Chinese Development Projects

Abstract Chinese aid comes with few strings attached, allowing recipient country leaders to use it for domestic political purposes. The vulnerability of Chinese aid to political capture has prompted speculation that it may be economically ineffective, or even harmful. We test these claims by estimating the effect of Chinese aid on subnational economic development—as measured by per-capita nighttime light emissions—and whether this effect is different at times a jurisdiction is favored politically. Contrary to the conventional wisdom, we do not find that the local receipt of Chinese aid undermines economic development outcomes at either the district level or provincial level. Nor does political favoritism in the allocation of Chinese aid towards the home regions of recipient country leaders reduce its effectiveness. Our results—from 709 provinces and 5,835 districts within 47 African countries between 2001 and 2012—demonstrate that Chinese aid improves local development outcomes, regardless of whether such aid is given to jurisdictions at times they are the birth region of the country’s leader.